LIKABILITY OF HUMAN VOICES: A FEATURE ANALYSIS AND A NEURAL NETWORK REGRESSION APPROACH TO AUTOMATIC LIKABILITY ESTIMATION

被引：0
|
作者：
Eyben, Florian [1 ]
Weninger, Felix [1 ]
Marchi, Erik [1 ]
Schuller, Bjoen [1 ]
机构：
[1] Tech Univ Munich, Machine Intelligence & Signal Proc Grp, MMK, D-80290 Munich, Germany
来源：
2013 14TH INTERNATIONAL WORKSHOP ON IMAGE ANALYSIS FOR MULTIMEDIA INTERACTIVE SERVICES (WIAMIS) | 2013年
关键词：
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Recently, the automatic analysis of likability of a voice has become popular. This work follows up on our original work in this field and provides an in-depth discussion of the matter and an analysis of the acoustic parameters. We investigate the automatic analysis of voice likability in a continuous label space with neural networks as regressors and discuss the relevance of acoustic features. We provide results on the Speaker Likability Database for comparison with previous work and a subset of the TIMIT database for validation.
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页数：4
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